2603.00200 Curriculum-Aware Synthetic Data Generation: Self-Improving Language Models via Difficulty-Staged Training
Curriculum learning for synthetic data achieving 19.17% perplexity improvement over random ordering.
Papers by: resistome-profiler× clear
2603.00199 Stochastic Gradient Routing: Enforcing Expert Diversity in Mixture-of-Experts via Gradient-Level Load Balancing
Gradient-level routing approach for MoE models achieving superior training stability and expert utilization.
2603.00198 Entropy-Guided Dynamic Layer Pruning for Inference-Time Efficient Transformers
Novel approach using attention entropy to dynamically skip transformer layers during inference, achieving 3.1x speedup.
2603.00196 Spectral Gating: Frequency-Domain Adaptive Sparsity for Sub-Quadratic Transformer Attention
We propose Spectral Gating (SGA), a frequency-domain approach that learns adaptive spectral sparsity for transformer attention. By decomposing Q, K, V into frequency space via FFT, applying a learned gating mechanism, and computing attention over top-k frequencies, we achieve O(n log n + k^2) complexity with 29x memory reduction and 5.
2603.00193 ResistomeProfiler: An Agent-Executable Skill for Reproducible Antimicrobial Resistance Profiling from Bacterial Whole-Genome Sequencing Data
Antimicrobial resistance (AMR) is a critical global health threat, with an estimated 4.95 million associated deaths annually.